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EBE 2174/EBQ2074 Econometrics Tutorial 2 (WE07 &WE09) Evan Lau

This document contains 4 questions from an econometrics tutorial about linear regression models. Question 3 provides a data set of driving experience and monthly auto insurance premiums for 8 drivers and asks the student to (a) identify the dependent and independent variables and expected relationship, (b) compute the coefficients β1 and β2 and write out the regression equation, and (c) interpret the coefficients. Question 4 asks the student to (a) list the assumptions of the simple linear regression model regarding the random error term and (b) write out the formulas for computing the coefficients β1 and β2 and calculating the slope of the regression line.

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151 views1 page

EBE 2174/EBQ2074 Econometrics Tutorial 2 (WE07 &WE09) Evan Lau

This document contains 4 questions from an econometrics tutorial about linear regression models. Question 3 provides a data set of driving experience and monthly auto insurance premiums for 8 drivers and asks the student to (a) identify the dependent and independent variables and expected relationship, (b) compute the coefficients β1 and β2 and write out the regression equation, and (c) interpret the coefficients. Question 4 asks the student to (a) list the assumptions of the simple linear regression model regarding the random error term and (b) write out the formulas for computing the coefficients β1 and β2 and calculating the slope of the regression line.

Uploaded by

Jaleany T C Khun
Copyright
© © All Rights Reserved
We take content rights seriously. If you suspect this is your content, claim it here.
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Download as DOCX, PDF, TXT or read online on Scribd
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EBE 2174/EBQ2074 Econometrics

Tutorial 2 (WE07 &WE09)


Evan Lau

Question 1
Explain how a classical linear regression model can be classified as the best linear unbiased estimator (BLUE).

Question 2
What is meant by the best unbiased or efficient estimator? Why is this important?

Question 3

A random sample of 8 drivers insured with a company and having similar into insurance policies was selected. The
following table lists their driving experience (in years) and monthly auto insurance premiums.

Driving Experience (years) Monthly Auto Insurance Premium ($)


5 64
2 87
12 50
9 71
15 44
6 56
25 42
16 60

(a) Does the insurance premium depend on the driving experience or does the driving experience depend on the
insurance premium? Do you expect a positive or a negative relationship between these two variables?
(b) Compute β 1 and β 2 and write out the estimation regression.
(c) Interpret β 1 and β 2.

Question 4
(a) Lists out the assumptions of the simple linear regression model in terms of the random error, e.
(b) Write out the formula for β 1 and β 2 and how does the slope of the regression line can be calculated?

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